ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Blind Color Image Steganalysis Based on Multi-Transform Combined Features Selected by a Hybrid of ANOVA and BPSO
1
8
EN
Mansoureh
Pezhmanpour
EE Dept. Islamic Azad University South Tehran Branch Tehran, Iran
Y
Mansour
Sheikhan
EE Dept. Islamic Azad University South Tehran Branch Tehran, Iran
N
Mohammad Shahram
Moin
Multimedia Sys. Group IT Dept. Iran Telecom Research Center Tehran, Iran
N
Steganalysis techniques have been classified into two major categories: blind steganalysis which is independent of the steganography method and specific steganalysis which attempts to detect specific steganographic media. Feature extraction is an important functional block in the steganalysis systems. The features are commonly in spatial domain or extracted from transform domains such as discrete wavelet transform (DWT), discrete cosine transform (DCT) or contourlet transform (CT). In this paper, a blind color image steganalysis method based on a hybrid set of features (statistical moments, entropy, and co-occurrence matrix features) extracted from a combination of DWT, DCT, and CT is proposed. The hybrid of "analysis of variation (ANOVA)" as an open-loop feature selection method, and "binary particle swarm optimization (BPSO)" as a closed-loop one, is used in this work to improve the detection rate in tandem with significant reduction in the size of feature set. Jsteg, OutGuess, JPHS and model-based steganography methods are attacked in this work. By using the hybrid of "ANOVA+BPSO", the number of features is reduced to 13. Empirical results show that the most discriminative features in clean/stego image classification are statistical moments of co-occurrence matrix of contourlet transform. The most discriminative selected features are fed into a nonlinear support vector machine (SVM) classifier to distinguish the cover and stego images. Average detection accuracy of the proposed model is above 81 percent for the embedding-rate ranges of 5% to 25%.
Steganalysis, entropy, statistical moments, DCT, DWT, contourlet, co-occurrence matrix
http://ijict.itrc.ac.ir/article-1-245-en.html
http://ijict.itrc.ac.ir/article-1-245-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Towards Faster Performance of PROMETHEE II in a Lower Class of Complexity
9
18
EN
Arash
Niknafs
Department of Information Technology Engineering Tarbiat Modares University Tehran, Iran
Y
Nasrollah
Moghaddam Charkari
Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran, Iran
N
Ali Akbar
Niknafs
Department of Computer Engineering Shahid Bahonar University of Kerman Kerman, Iran
N
PROMETHEE II is one of the most popular members of the well-known family of multi-criteria decision making methods. One of the main concerns in developing PROMETHEE-based systems is the rapid growth of the response time as the number of alternatives (n) and criteria (k) grow. PROMETHEE II belongs to the computational complexity class of O(n توان 2). In this paper, a simplified version of PROMETHEE II is proposed and a novel estimation of the simplified PROMETHEE II is introduced. This simplified version reproduces the results of the original method and requires fewer operations. The estimation belongs to the complexity class of O(n log n) and consequently has a shorter response time than that of the simplified version. The proposed simplification and estimation are tested and evaluated with real-world data. When compared to the original PROMETHEE II and even other similar MCDM methods, such as AHP, ELECTRA, and TOPSIS, the experiments reveal the satisfactory results with a considerably reduced computational complexity and response time.
multi criteria decision making, PROMETHEE II, decision support systems, recommender systems
http://ijict.itrc.ac.ir/article-1-246-en.html
http://ijict.itrc.ac.ir/article-1-246-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Document Classification Using Novel Competitive Neural Text Classifier
19
31
EN
Seyyed Mohammad Reza
Farshchi
Artificial Intelligence Department, and Advance Research Center (ARC) Islamic Azad University Mashhad Branch, Iran
Y
Mohammad Bagher
Naghibi Sistani
Electrical Engineering Department Ferdowsi University of Mashhad Mashhad, Iran
N
Text categorization is one of the well studied problems in data mining and information retrieval. Given a large quantity of documents in a data set where each document is associated with its corresponding category. This research proposes a novel approach for English and Persian documents classification with using novel method that combined competitive neural text categorizer with new vectors that we called, string vectors. Traditional approaches to text categorization require encoding documents into numerical vectors which leads to the two main problems: huge dimensionality and sparse distribution. Although many various feature selection methods are developed to address the first problem, the reduced dimension remains still large. If the dimension is reduced excessively by a feature selection method, robustness of document categorization is degraded. The idea of this research as the solution to the problems is to encode the documents into string vectors and apply it to the novel competitive neural text categorizer as a string vector. Extensive experiments based on several benchmarks are conducted. The results indicated that this method can significantly improve the performance of documents classification up to 13.8% in comparison to best traditional algorithm on standard Reuter 21578 dataset.
Data mining, text categorization, vector based model, competitive neural text categorizer
http://ijict.itrc.ac.ir/article-1-247-en.html
http://ijict.itrc.ac.ir/article-1-247-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Sequential Interference-Aware Admission Control in Underlay Cognitive Radio Networks
33
40
EN
Masoumeh
Farmahini Farahani
Communication Technology Faculty Iran Telecommunication Research Center (ITRC) Tehran, Iran
Y
Abdorasoul
Ghasemi
Faculty of Electrical and Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran
N
Seyyed Mohammad
Razavizadeh
Department of Electrical Engineering, Iran University of Science and Technology (IUST) Tehran, Iran
N
In this paper, a new joint admission and power control scheme is introduced for wireless cognitive radio networks. It is assumed that the Cognitive Users (CUs) arrive sequentially in time and exploit the spectrum simultaneous to the licensed primary users. The objective is to minimize the blocking probability of the new arriving CUs while the interference limit constraint of primary users is not violated and the quality of service (QoS) requirements of the current admitted CUs is satisfied. To these aims, an algorithm is developed for CUs admission in which the power of the new arriving CU gradually increases according to two predefined parameters, Primary Interference Margin (PIM) and Secondary Interference Margin (SIM). In addition to protect the QoS of the current CUs, their powers are boosted by a particular parameter, which is calculated based on PIM and their maximum allowable power. Moreover, the PIM guarantees the protection of the primary users during the admission phase of the new arriving CU. Two admission control algorithms have been proposed, a safe admission which tightly admits a new CU and a moderate one which loosely accepts a new CU. Simulation results are provided to evaluate the performance of the proposed algorithms in terms of the blocking and outage probability and compared with recent proposed schemes. These results show that the proposed algorithms outperform the similar schemes while they are more suitable for a practical scenario.
Cognitive Radio Network, Underlay Transmission, Admission Control, Power Control
http://ijict.itrc.ac.ir/article-1-248-en.html
http://ijict.itrc.ac.ir/article-1-248-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
VE Architect-Driven Service-Oriented Business Network Process Realization
41
53
EN
Alireza
Khoshkbarforoushha
Dept. of Information Technology Engineering Tarbiat Modares University Tehran, Iran
Y
Mohammad
Aghdasi
Dept. of Information Technology Engineering Tarbiat Modares University Tehran, Iran
N
Mehrnoush
Shamsfard
Electrical and Computer Engineering Faculty Shahid Beheshti University GC Tehran, Iran
N
Business opportunities are not permanent. Enterprises to instantly meet them collaborate with each other through realizing business network processes (BNP) in which their activities are done with various partners within a network. Recently, these business network processes are enabled with Service-Oriented technologies, that we call them Service-Oriented Business Network Process (SOBNP). In today's dynamic and changing environment Virtual Enterprise (VE) architects require a flexible framework through which they could design and realize SOBNP instantly. In this theme, there exist a number of frameworks that constitute the SOBNP, but they almost neglect two salient issues: a) Covering and incorporating high-level (i.e. business level) and low-level (i.e. technical level) requirement in business process creation; b) Adjusting to the VE architect without deep knowledge of computer science. Thus, the main objective of this paper is to propose a framework and related tools and techniques to constitute SOBNP, as a main building block of Instant Virtual Enterprise (IVE), which address two above-mentioned issues. The framework namely SOBNP Realization consists of three phases including requirements specification, ontology-based partner search and selection, and BPEL (Business Process Execution Language) process synthesis. A prototype system is implemented to demonstrate the concept of VE architect-driven SOBNP realization in IVE.
Semi-automatic realization of business network process, Service-oriented Business Network Process, Ontology-based partner selection, Instant virtual enterprise, BPEL process
http://ijict.itrc.ac.ir/article-1-249-en.html
http://ijict.itrc.ac.ir/article-1-249-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Improving the Performance of Proposed Multi-Agent Domain Specific Search Engine Using Query Refinement Component
69
78
EN
Elmira
Hajimani
Electrical and Computer Eng. Faculty Shahid Beheshti University Tehran, Iran
Y
Eslam
Nazemi
Electrical and Computer Eng. Faculty Shahid Beheshti University Tehran, Iran
N
The web size is increasing continuously. The more the Internet is growing; the more tendencies the people have to use the search engines. Moreover, since most of the commercial search engines are based on keyword indexing, there are many records in their result lists that are irrelevant to the user's information needs. It is shown that for retrieving more relevant and precise results, the following two points should be concerned: First of all, the query (either it is generated by a human or an intelligent agent) should be expressed in an accurate and exact manner. Second, we should empower search engines with the ability to capture the semantic relation between the words and the query context. Hence, different search engine architectures, each of which containing query refinement or semantic understanding components, have been proposed. Each architectural model has its own specific properties; but, most of them focus on only one of the two points mentioned above to improve the overall system efficiency. Moreover, in existing architectures, query refinement components have direct interaction with users which may either take their time or threat their privacy while gathering basic information. In this paper, we proposed an improved architectural model for agent and ontology based search engine which uses domain ontology for semantic understanding and a query refinement subsystem based on fuzzy ontology. This subsystem helps Search Agents to refine their queries, express them in a more precise way and get more relevant results. The simulation result shows that using this query refinement subsystem by Search Agents can improve the system efficiency up to 5.2%.
Search engines, Domain ontology, Fuzzy ontology, intelligent agents, query refinement
http://ijict.itrc.ac.ir/article-1-250-en.html
http://ijict.itrc.ac.ir/article-1-250-en.pdf
ICT Research Institute(ITRC)
International Journal of Information and Communication Technology Research
2251-6107
2783-4425
2
4
2010
12
1
Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator
79
87
EN
Javad
Basiri
School of Electrical and Computer Engineering College of Engineering University of Tehran, Tehran, Iran
Y
Azadeh
Shakery
School of Electrical and Computer Engineering University of Tehran Tehran, Iran
N
Behzad
Moshiri
Control & Intelligent Processing Center of Excellence, School of ECE University of Tehran Tehran, Iran
N
Morteza
Zihayat
School of Electrical and Computer Engineering University of Tehran Tehran, Iran
N
Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering and content-based filtering. This study proposes a new hybrid recommender system that focuses on improving the performance under the "new user cold-start" condition where existence of users with no ratings or with only a small number of ratings is probable. In this method, the optimistic exponential type of ordered weighted averaging (OWA) operator is applied to fuse the output of five recommender system strategies. Experiments using MovieLens dataset show the superiority of the proposed hybrid approach in the cold-start conditions.
OWA, hybrid approach, demographic- information, content-based filtering, collaborative filtering, recommender system
http://ijict.itrc.ac.ir/article-1-251-en.html
http://ijict.itrc.ac.ir/article-1-251-en.pdf